| dc.description.abstract | Purpose - The purpose of present study is to propose a state-of-the-art new approach to enhance assessment capabilities of failure mode and effects analysis (FMEA); and demonstrates it through practical examples to show how relative failure rankings can be determined and to identify improving scales for failure modes. Subsequently provides helpful managerial implications for management.
Methodology - Failure mode and effects analysis (FMEA) offers a quick and easy way for identifying ranking-order for all failure modes in a system or a product. In FMEA the ranking methods is so called risk priority number (RPN), which is a mathematical product of severity (S), occurrence (O), and detection (D). The SODs are input criteria where S is the seriousness of the effect of the failure. The second input is O, which is the probability or frequency of the failure. The third input is D, which is the probability of failure being detected before the impact of the effect is realized. One of major disadvantages of this ranking-order is that the failure mode with different combination of SODs may generate same RPN resulting in difficult decision-making. Another shortfall of FMEA is lacking of discerning contribution factors, which lead to insufficient information about scaling of improving effort. Through data envelopment analysis (DEA) technique and its extension, the proposed approach evolves the current rankings for failure modes by exclusively investigating SOD in lieu of RPN and to furnish with improving scales for SOD. To demonstrate how DEA is implemented to enhance FMEA, the paper examines two real case examples origin in FMEA setting. One is computer software coding where failure could happen during execution if process of coding shall incomplete. The case demonstrates how DEA is applied on existing FMEA. The other case is healthcare discipline where failure could arise if surveillance measures did not fully implement and execute. This case is to provide risk management in healthcare through integration of FMEA and DEA.
Findings - By demonstrating an illustrative example and extended case study, the proposed approach supports that DEA can not only complement traditional FMEA for improving assessment capability but also, especially, to provide corrective information regarding the failure factors – severity, occurrence and detection. Further application of DEA extensions also reveals that the utilization of this methodology is useful to managing resource allocation and risk management.
Practical implications – It is shown that the proposed approach enables manager/designers to prevent system or product failures at early stage of design. Moreover the approach is able to provide managerial insight of SOD more effectively rather than justifying the efforts on RPN alone. Projection of each SOD is determined to help manager examine scale of efforts. Finally the stratification analysis offers the economical allocations of failure modes with respect to the incurred costs and the efficiency.
Originality/value – The paper proposes a state-of-the-art new approach, robust, structured and useful in practice, for failure analysis. The methodology, within a firmed methodology, overcomes some of the largely known shortfalls of traditional FMEA: it takes into account multiple criteria and restricted weighted; and it analyses the failure modes’ ranking considering not only the direct impacts of failure indexes, but also the contribution of these indexes. The paper also provides worthwhile future research directions.
| en_US |